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BACH-AI-Tools

Fresh Linkedin Profile Data MCP Server

Detect Activity Time

detect_activity_time

Identify when a LinkedIn profile was last active by passing its URL, revealing the recency of user engagement.

Instructions

Get the time of the latest profile activity. 2 credits per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
linkedin_urlYesExample value: https://www.linkedin.com/in/williamhgates/

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv2.0.0

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does disclose cost ('2 credits per call'), which is useful, but it does not explain what 'activity' includes, what the returned time format is, whether the profile must be public, or whether the operation is read-only beyond the implied 'Get'.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no filler. The first sentence front-loads the action and resource, and the second provides the cost detail. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple with one well-specified parameter, so the input side is adequately covered. However, with no output schema and no annotations, the description should at least hint at the return format or semantics of 'time'. It is minimally viable but missing key details that would help an agent know exactly what to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is high (100%), so the baseline is 3. The input schema provides an example value for linkedin_url, but no prose definition of the parameter. The tool description itself adds no additional meaning to the parameter, leaving the example as the only guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the resource ('latest profile activity') and the action ('Get the time'), which is a specific and recognizable operation. It doesn't explicitly distinguish itself from the sibling tool get_profile_latest_post_date, which could overlap semantically, but the core purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance about when to use this tool versus alternatives such as get_profile_latest_post_date, get_open_to_work_status, or get_years_of_experience. The cost note '2 credits per call' is not usage guidance. No context is given for choosing or excluding this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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